The slides that will accompany my live webcast for OpenCon 2014 attendees, all about open data in research. The benefits, the how to (both legally & technically), examples, pitfalls, and the future of open research data.

1. Intro to Open Data
for OpenCon 2014
November 4, 2014
Ross Mounce, Ph.D. (@RMounce)
Postdoc, University of Bath

2. These slides are on Slideshare here:
bit.ly/opendataintro
All textual content is

3. With thanks to SPARC & R2RC for organising this webcast series
Previous talks in this series have been given on
Open Access http://youtu.be/5YwASIziPIQ
and
Open Educational Resources http://youtu.be/5Dauh_PeAzI

4. Outline
●Why care about data?
●Definition: exactly what is open data?
●Open data in scholarship, and beyond...
● Aspects of open data, inc. HowTo
● Legal , Technical
● Privacy! Not all data should be be open
● The 5 stars of open data

5. Why care about data?
Data is absolutely fundamental to most research
Science without data isn't science *
*Entirely theoretical, data-free contributions to science are possible, but rare

7. By sharing data we can see further
Data are the building blocks of
science
Shared, re-used data allow us to
more rigorously test hypotheses;
“to see further”
...and to do it all more quickly and
easily.
Also, for validation & reproducibility
(more of which later...)

8. What exactly is open data?
Open means anyone can
freely access, use, modify,
and share for any purpose
(subject, at most, to requirements
that preserve provenance and
openness)
From http://opendefinition.org/,
see http://opendefinition.org/od/ for more detail

9. Legally, what is open data?
There are a great many open knowledge definition (OKD) conformant licences,
including:
CC0
http://creativecommons.org/
publicdomain/zero/1.0/
CC BY
https://creativecommons.org/
licenses/by/4.0/
CC BY-SA
https://creativecommons.org/
licenses/by-sa/4.0/
See here for the comprehensive list: http://opendefinition.org/licenses/

10. Not all Creative Commons licences are
'open'
} NC -- You “may not use this work for
commercial purposes”.
Work under this licence cannot be used
for any purpose, therefore it is not open.
Can have significant, often unexpected
negative impact on potential re-use.
ND -- “No Derivative Works”.
Work under this licence cannot be
adapted if it is re-used. Not very helpful
for research!
NC & ND – An extremely restrictive re-use
licence, neither commercial purposes nor
adaptations are allowed.

11. Non-open licencing causes real
problems for research & education
The Creative Commons non-commercial (-NC) restriction is poorly defined in
most jurisdictions, and even more poorly understood by many of its users.
“non-commercial” != “non-profit”
A) Non-commercial actually excludes many teaching purposes:
In the UK, university students typically pay expensive tuition fees to attend.
Thus university teaching is often a commercial activity, -NC restricted
materials cannot be used to teach students in these circumstances.
B) Licence incompatibility – NC licences are not compatible with licences
used on major collaboration platforms like Wikipedia or Wikimedia Commons
C) Non-commercial organizations (e.g. Deutschlandradio)
have been successfully sued for re-using CC BY-NC
content without permission.
http://zookeys.pensoft.net/articles.php?id=3036
https://www.techdirt.com/articles/20140326/11405526695/german-court-says-creat
ive-commons-non-commercial-licenses-must-be-purely-personal-use.shtml

12. Real problems of non-open data:
GBIF & biodiversity data
Desmet, P. (2013) Showing you this map of aggregated bullfrog occurrences
would be illegal http://peterdesmet.com/posts/illegal-bullfrogs.html

13. Open data in scholarship, and beyond
The open data movement is much broader than just academia/research
It's been successful & popular in areas like open government data:
For transparency, detecting & discouraging corruption
For releasing social & commercial value (governments collect a lot of data
already, why not make wider use of it, at little or no extra cost?)
For participatory governance –
citizens can be more informed, a “read/write” society
Each of these has clear parallels with open
research data: transparency & fraud detection,
extra value through research data re-use,
participatory citizen science
Some text adapted from http://opengovernmentdata.org/

14. Open data in scholarship, and beyond
Similarly, and with some overlap to open research data,
there's the open GLAM movement
(GLAM = Galleries, Libraries, Archives & Museums)
In this case, their data is typically collections metadata
but also digital images of their collections
See http://openglam.org/ for more

15. Technical aspects of open data
So, you understand the imporance of licensing...
What next?
How best can we make our data openly available?
Where should I upload to?
What format(s) should I make the data available in?

16. Data Standards & Data File Formats
Adhere to existing standards!

17. Data Standards & Data File Formats
Take note of community standards:
e.g. the Bermuda Principles for sharing DNA seq. data
● Automatic release of sequence
assemblies larger than 1 kb
(preferably within 24 hours).
● Immediate publication of finished
annotated sequences.
● Aim to make the entire sequence
freely available in the public domain

18. Data Standards & Data File Formats
If there are no formally agreed community standards,
canvas the community to create/formalise a standard
e.g. Best Practices for Data Sharing in Phylogenetic Research
(2014) PLOS Currents Tree of Life
e.g. The 1st Open Economics International Workshop
(Cambridge, 2013) bringing together academic
economists from around the world to discuss data
sharing in economics research.

19. Data Standards & Data File Formats
If there are multiple, competing file formats:
Opt for file formats based on open standards
https://en.wikipedia.org/wiki/Open_standard
e.g.
Avoid proprietary formats
https://en.wikipedia.org/wiki/Proprietary_format
e.g.

21. Data Standards & Data File Formats
A real example: recent creation of a new data
standard for exchange of 3-dimensional reconstruction
of objects from tomographic imaging data
SPIERS software
+ VAXML data standard
Sutton et al (2012) SPIERS and VAXML: A software
toolkit for tomographic visualisation and a format for
virtual specimen interchange.
Palaeontologia Electronica

22. Where to upload open data?
http://www.crystallography.net/
Genbank,
SRA,
1000's more!

23. 'Data paper' journals
http://www.mdpi.com/journal/data/about

24. Your data is NOT 'too big' to share
http://gigadb.org/dataset/100124
39 Gigabytes (GB)
of MRI scans

25. Intelligent data papers allow databases
to automatically pull-in your data
Many publishers (e.g. Pensoft) intelligently
markup data papers so that the data can be
automatically ingested into appropriate db's
on the day of publication!
Data
data

26. Data sharing benefits authors & re-users
Piwowar HA, Vision TJ. (2013)
Data reuse and the open data
citation advantage. PeerJ
1:e175
“...open data citation
benefit for this sample
to be 9%”
relative to papers
providing no public
data, for gene
expression microarray
data
10.7717/peerj.175/fig-2
See also previous work by
Piwowar:
10.1371/journal.pone.0000308

27. Those who share data, do better science
Wicherts, J. M., Bakker, M. & Molenaar, D. (2011)
Willingness to share research data is related to the
strength of the evidence and the quality of reporting of
statistical results. PLoS ONE 6, e26828+ URL
http://dx.doi.org/10.1371/journal.pone.0026828
The authors examined psychological papers for the quality of statistical
reporting & asked the authors of those papers for the full data underlying
the reported results. Generally, those who shared, had more statistically
robust, reproducible results.

28. “Email the author for data” - doesnt work
A well-known problem, which
I myself have also faced
many times!!!
Many legacy journals
unfortunately still pretend
that “email the author” is
still acceptable.
Wicherts JM, Borsboom D,
Kats J, Molenaar D (2006)
The poor availability of
psychological research
data for reanalysis.
American Psychologist 61:
726–728 link

29. Best practice open data is time consuming
(but still worth the extra effort!)
Emilio M. Bruna recently provided an estimate of the amount of
time it took him to prepare & upload open data related to
publication to figshare & dryad.
11
Hours
& $90
(for Dryad)
Providing open-source code was the most time consuming part (25.5 hours),
and Open Access publication the most expensive ($600).
http://brunalab.org/blog/2014/09/04/the-opportunity-cost-of-my-openscience-was-35-
hours-690/

30. Not all data should be open!
Obviously, there are some types of
data which should NOT be made
mandatorily open e.g. sensitive
medical data
However, with informed consent, if patients really want to,
they should be allowed to publish their own medical data

31. But with informed consent, sharing
sensitive health data can have good
outcomes
http://blog.ted.com/2013/06/14/why-i-opensourced-cures-for-my-cancer-sa
lvatore-iaconesi-at-tedglobal-2013/

32. Other exceptions to the open default
Sensitive species conservation data
e.g. exact geocoordinates of home range
Certain species of wild orchids, cacti & carnivorous plants
are highly endangered by illegal harvesting.
Publishing the exact geolocation data of the remaining
populations of commercially-desirable, endangered
species is really dumb thing to do.
Such data is typically held privately in databases (not
publicly available).

33. The 5 stars of open data
Most research data would get
ZERO (not available online)
Or just ONE star
http://5stardata.info/

34. 3-star open research data is achievable
This is where research data publication
should be aiming for in the short term.
Publishing .csv / non-proprietary open data is
NOT actually that hard!
http://5stardata.info/

35. Open Access & Open Data have similar goals
80% of research is publicly
funded
1
e.g. maximising the return on investment, provided to research by
taxpayers and charities
Source: “Academic Publishing: Survey of funders supports the benign Open Access outcome priced into shares, HSBC Global Research,”
February 11, 2013: https://www.research.hsbc.com/midas/Res/RDV?ao=20&key=RxArFbnG1P&n=360010.PDF

36. Further Reading
1.Editor’s Introduction - Samuel A. Moore
2.Open Content Mining - Peter Murray-Rust,
Jennifer C. Molloy, Diane Cabell
3.The Need to Humanize Open Science - Eric C.
Kansa
4.Data Sharing in a Humanitarian Organization: The
Experience of Médecins Sans Frontières - Unni
Karunakara
5.Why Open Drug Discovery Needs Four Simple
Rules for Licensing Data and Models - Antony J.
Williams, John Wilbanks, Sean Ekins
6.Open Data in the Earth and Climate Sciences -
Sarah Callaghan
7.Open Minded Psychology - Wouter van den Bos,
Mirjam Jenny, Dirk Wulff
8.Open Data in Health Sciences - Tom Pollard
9.Open Research Data in Economics - Velichka
Dimitrova
10.Open Data and Palaeontology - Ross Mounce
Out soon this November,
2014
Published by Ubiquity
Press

37. Further Reading
● The Open Data Handbook - http://opendatahandbook.org/
● 5 star Open Data - http://5stardata.info/
● Science as an open enterprise (2012) A Royal Society report
● Caetano, D. S. & Aisenberg, A. 2014 Forgotten treasures: the fate of data in animal
behaviour studies Animal Behaviour
Data sharing in phylogenetics
● Magee et al 2014 The Dawn of Open Access to Phylogenetic Data PLOS ONE
● Drew et al 2013 Lost Branches on the Tree of Life. PLOS Biology
● Stoltzfus et al 2012 Sharing and re-use of phylogenetic trees (and associated data)
to facilitate synthesis. BMC Research Notes
On licencing & legal issues with re-use
● Hagedorn et al 2011 Creative commons licenses and the non-commercial
condition: Implications for the re-use of biodiversity information. ZooKeys
● Mounce 2012. Life as a palaeontologist: Academia, the internet and creative
commons. Palaeontology Online
● Klimpel, P. 2012 Consequences, Risks, and side-effects of the license module
Non-Commercial – NC [PDF]

38. Further Reading
● Murray-Rust, P. Open data in science. Serials Review 34, 52-64 (2008). URL
http://dx.doi.org/10.1016/j.serrev.2008.01.001
● Leonelli, S., Smirnoff, N., Moore, J., Cook, C. & Bastow, R. Making open data work
for plant scientists. Journal of Experimental Botany 64, 4109-4117 (2013). URL
http://dx.doi.org/10.1093/jxb/ert273
● Hrynaszkiewicz, I. & Cockerill, M. Open by default: a proposed copyright license
and waiver agreement for open access research and data in peer-reviewed
journals. BMC Research Notes 5, 494+ (2012). URL
http://dx.doi.org/10.1186/1756-0500-5-494
● Boulton, G., Rawlins, M., Vallance, P. & Walport, M. Science as a public enterprise:
the case for open data. The Lancet 377, 1633-1635 (2011). URL
http://dx.doi.org/10.1016/s0140-6736(11)60647-8
● Parr, C. S. Open sourcing ecological data. BioScience 57, 309-310 (2007). URL
http://dx.doi.org/10.1641/b570402
● Poisot, T., Mounce, R. & Gravel, D. Moving toward a sustainable ecological
science: don't let data go to waste! Ideas in Ecology and Evolution 6 (2013). URL
http://dx.doi.org/10.4033/iee.2013.6b.14.f

39. November 15-17, 2014
Washington, D.C. & Online
www.opencon2014.org
@open_con #opencon2014
See you there if you're lucky enough to be going!

40. Thank you!
Happy to answer all questions
ross@righttoresearch.org
@RMounce
www.righttoresearch.org
www.sparc.arl.org